Cache Food Nutrition API Responses With Redis

Every duplicate search for "banana" bills your quota. Cache food nutrition API responses Redis on your backend proxy cuts costs 30 to 70% for typical calorie apps.

What to Cache

Node.js Example

import Redis from 'ioredis';
const redis = new Redis(process.env.REDIS_URL);

async function cachedSearch(q, limit) {
  const key = `search:${q.toLowerCase()}:${limit}`;
  const hit = await redis.get(key);
  if (hit) return JSON.parse(hit);

  const data = await upstreamCalorieApiSearch(q, limit);
  await redis.setex(key, 600, JSON.stringify(data));
  return data;
}

Place cache on your proxy, not inside mobile apps (stale data risk across users is fine for public food facts).

Cache Invalidation

Food catalog changes slowly. Long TTL on barcode is safe. Short TTL on search handles new products.

Memory Sizing

Rough guide: 10,000 cached search responses × 5 KB ≈ 50 MB. Start with Upstash or Redis Cloud free tier.

Combine With Client Tactics

• Debounce suggest
• AsyncStorage recents on mobile
• Backend proxy rate limits

When Not to Cache

• Personalized nutrition coaching calculations with user-specific overrides
• Real-time inventory (not applicable to Calorie API)

Docs | Register